A Bio-Conjugated Fullerene as a Subcellular-Targeted and Multifaceted Phototheranostic Agent

Fullerenes are candidates for theranostic applications because of their high photodynamic activity and intrinsic multimodal imaging contrast. However, fullerenes suffer from low solubility in aqueous media, poor biocompatibility, cell toxicity, and a tendency to aggregate. C₇₀@lysozyme is introduced herein as a novel bioconjugate that is harmless to a cellular environment, yet is also photoactive and has excellent optical and optoacoustic contrast for tracking cellular uptake and intracellular localization. The formation, water-solubility, photoactivity, and unperturbed structure of C₇₀@lysozyme are confirmed using UV-visible and 2D ¹H, ¹⁵N NMR spectroscopy. The excellent imaging contrast of C₇₀@lysozyme in optoacoustic and third harmonic generation microscopy is exploited to monitor its uptake in HeLa cells and lysosomal trafficking. Last, the photoactivity of C₇₀@lysozyme and its ability to initiate cell death by means of singlet oxygen (¹O₂) production upon exposure to low levels of white light irradiation is demonstrated. This study introduces C₇₀@lysozyme and other fullerene-protein conjugates as potential candidates for theranostic applications.     

Neural network-based flight control systems: Present and future

As the first review in this field, this paper presents an in-depth mathematical view of Intelligent Flight Control Systems (IFCSs), particularly those based on artificial neural networks. The rapid evolution of IFCSs in the last two decades in both the methodological and technical aspects necessitates a comprehensive view of them to better demonstrate the current stage and the crucial remaining steps towards developing a truly intelligent flight management unit. To this end, in this paper, we will provide a detailed mathematical view of Neural Network (NN)-based flight control systems and the challenging problems that still remain. The paper will cover both the model-based and model-free IFCSs. The model-based methods consist of the basic feedback error learning scheme, the pseudocontrol strategy, and the neural backstepping method. Besides, different approaches to analyze the closed-loop stability in IFCSs, their requirements, and their limitations will be discussed in detail. Various supplementary features, which can be integrated with a basic IFCS such as the fault-tolerance capability, the consideration of system constraints, and the combination of NNs with other robust and adaptive elements like disturbance observers, would be covered, as well. On the other hand, concerning model-free flight controllers, both the indirect and direct adaptive control systems including indirect adaptive control using NN-based system identification, the approximate dynamic programming using NN, and the reinforcement learning-based adaptive optimal control will be carefully addressed. Finally, by demonstrating a well-organized view of the current stage in the development of IFCSs, the challenging issues, which are critical to be addressed in the future, are thoroughly identified. As a result, this paper can be considered as a comprehensive road map for all researchers interested in the design and development of intelligent control systems, particularly in the field of aerospace applications.     

基于DSP的智能电源控制单元设计与实现

本文利用TI公司TMS320F28335芯片高效的浮点运算能力,结合片上丰富的外设,设计并实现了一种具有高可靠性的智能电源控制单元。该控制单元周期性地对各片上外设进行自检维护,完成多路负载通道控制、电压、电流的实时监控,并对故障进行指示、处理和上报,同时提供人机交互界面更新状态信息。经过验证,该控制单元工作稳定,具备良好的工程应用价值。     

Utilizing sensor data to model students’ creativity in a digital environment

While creativity is essential for developing students’ broad expertise in Science, Technology, Engineering, and Math (STEM) fields, many students struggle with various aspects of being creative. Digital technologies have the unique opportunity to support the creative process by (1) recognizing elements of students’ creativity, such as when creativity is lacking (modeling step), and (2) providing tailored scaffolding based on that information (intervention step). However, to date little work exists on either of these aspects. Here, we focus on the modeling step. Specifically, we explore the utility of various sensing devices, including an eye tracker, a skin conductance bracelet, and an EEG sensor, for modeling creativity during an educational activity, namely geometry proof generation. We found reliable differences in sensor features characterizing low vs. high creativity students. We then applied machine learning to build classifiers that achieved good accuracy in distinguishing these two student groups, providing evidence that sensor features are valuable for modeling creativity.     

Isolation of antimicrobial agent from the marine algae Cystoseira hakodatensis

Cystoseira hakodatensis is an unutilised brown algae belonging to family Sargassaceae. A crude methanol extract from the algae showed inhibitory effects on the growths of Bacillus cereus and Bacillus licheniformis. To isolate the major antimicrobial agent, a sequential active‐guided isolation procedure was applied: liquid–liquid extraction, column chromatography and bio‐autography. A marked antimicrobial agent (active α) was isolated in hydrophobic fraction and was determined to phenolics without carbohydrates and proteins by phytochemical test. Regarding the antimicrobial potential, the isolated active α showed better inhibitory effects against B. cereus and B. licheniformis at 2 and 4 times of lower concentrations (62.5 and 31.3 μg mL^?1) in comparison with epigallocatechin gallate. These results showed that C. hakodatensis is a potential source of antimicrobial agent capable of preventing the growth of the two bacteria.     

A three-dimensional surface measurement system implemented with Gaussian process based adaptive sampling

Self-adaptive surface measurements that can reduce data redundancy and improve time efficiency are in high demand in many fields of science and technology. For this purpose, a system implemented with Gaussian process (GP) adaptive sampling is developed. The non-parametric GP model is applied to reconstruct the topography and guide the subsequent sampling position, which is determined from the inference uncertainty estimation. A criterion is proposed to terminate the GP adaptive measurement automatically without any prior model or data of the topography. Experiments on typical surfaces validate the intelligence, adaptability, and high accuracy of the GP method along with the stabilization of the automatic iteration termination. Compared with traditional raster sampling, data redundancy is reduced and the time efficiency is improved without sacrificing the surface reconstruction accuracy. The proposed method can be implemented in other systems with similar measurement principles, thus benefitting surface characterizations.     

A Complexing Agent to Enable a Wide-Temperature Range Bromine-Based Flow Battery for Stationary Energy Storage

Bromine-based flow batteries (Br-FBs) are considered one of the most promising energy storage systems due to their features of high energy density and low cost. However, they generally suffer from uncontrolled diffusion of corrosive bromine particularly at high temperatures. That is because the interaction between polybromide anions and the commonly used complexing agent (N–methyl–N–ethyl–pyrrolidinium bromide [MEP]) decreases with increasing temperatures, which causes serious self-discharge and capacity fade. Herein, a novel bromine complexing agent, 1–ethyl–2–methyl–pyridinium bromide (BCA), is introduced in Br-FBs to solve the above problems. It is proven that BCA can combine with polybromide anions very well even at a high temperature of 60 °C. Moreover, the BCA contributes to decreasing the electrochemical polarization of Br⁻/Br₂ couple, which in turn improves their power density. As a result, a zinc–bromine flow battery with BCA as the complexing agent can achieve a high energy efficiency of 84% at 40 mA cm⁻², even at high temperature of 60 °C and it can stably run for more than 400 cycles without obvious performance decay. This paper provides an effective complexing agent to enable a wide temperature range Br-FB.     

Biologically Inspired Design of Context-Aware Smart Products

The rapid development of information and communication technologies (ICTs) and cyber–physical systems (CPSs) has paved the way for the increasing popularity of smart products. Context-awareness is an important facet of product smartness. Unlike artifacts, various bio-systems are naturally characterized by their extraordinary context-awareness. Biologically inspired design (BID) is one of the most commonly employed design strategies. However, few studies have examined the BID of context-aware smart products to date. This paper presents a structured design framework to support the BID of context-aware smart products. The meaning of context-awareness is defined from the perspective of product design. The framework is developed based on the theoretical foundations of the situated function–behavior–structure ontology. A structured design process is prescribed to leverage various biological inspirations in order to support different conceptual design activities, such as problem formulation, structure reformulation, behavior reformulation, and function reformulation. Some existing design methods and emerging design tools are incorporated into the framework. A case study is presented to showcase how this framework can be followed to redesign a robot vacuum cleaner and make it more context-aware.     

Recent Development of Photothermal Agents (PTAs) Based on Small Organic Molecular Dyes

Photothermal therapy (PTT) has attracted great attention due to its noninvasive and effective use against cancer. Various photothermal agents (PTAs) including organic and inorganic PTAs have been developed in the last decades. Organic PTAs based on small-molecule dyes exhibit great potential for future clinical applications considering their good biocompatibility and easy chemical modification or functionalization. In this review, we discuss the recent progress of organic PTAs based on small-molecule dyes for enhanced PTT. We summarize the strategies to improve the light penetration of PTAs, methods to enhance their photothermal conversion efficiency, how to optimize PTAs’ delivery into deep tumors, and how to resist photobleaching under repeated laser irradiation. We hope that this review can rouse the interest of researchers in the field of PTAs based on small-molecule dyes and help them to fabricate next-generation PTAs for noninvasive cancer therapy.     

Structure−Activity Relationships of Cinnamate Ester Analogues as Potent Antiprotozoal Agents

Protozoal infections are still a global health problem, threatening the lives of millions of people around the world, mainly in impoverished tropical and sub-tropical regions. Thus, in view of the lack of efficient therapies and increasing resistances against existing drugs, this study describes the antiprotozoal potential of synthetic cinnamate ester analogues and their structure-activity relationships. In general, Leishmania donovani and Trypanosoma brucei were quite susceptible to the compounds in a structure-dependent manner. Detailed analysis revealed a key role of the substitution pattern on the aromatic ring and a marked effect of the side chain on the activity against these two parasites. The high antileishmanial potency and remarkable selectivity of the nitro-aromatic derivatives suggested them as promising candidates for further studies. On the other hand, the high in vitro potency of catechol-type compounds against T. brucei could not be extrapolated to an in vivo mouse model.